Visualization and Correlation Analysis of Learning Engagement Based on Multimodal Data in Collaborative Programming:Understanding the Interplays Among Behavioral,Cognitive,Social,and Emotional Dimensions and Their Impacts on Learning
Visualization and Correlation analyses of students'engagement based on multimodal data can effectively implement accurate evaluation of collaborative learning.To delve into the intricate mechanisms how group structures influence learning engage-ment,an analytical framework and coding scheme for multimodal collaborative learning engagement are constructed,covering stu-dents'behaviors,cognition,social interactions,and emotions.Utilizing this coding framework,multimodal data from 66 participants at H University,including interactive audio-video recordings,coding screen captures and code texts,are collected,coded and analyzed by using Nivivo.The diverse learning engagement and academic performance among collaborative groups with various structural fea-tures are visualized by using R tools.The complex intrinsic connections within each collaborative learning engagement dimension and their impacts on learning achievements are exploredby using Pearson correlation analysis.The research shows that the evaluation of collaborative learning,the implementation of precise intervention and the promotion of knowledge construction provide scientific basis.The research on this problem can provide reference for exploring collaborative learning input from multiple perspectives.
国家科技期刊平台
NSTL
万方数据
